Many studies demonstrate that memory deficit and cerebrospinal fluid markers of amyloid and tau are predictive of incident dementia. These markers have even been proposed as new diagnostic criteria for Alzheimer's disease and as outcome measures in clinical trials. Yet these studies have largely been conducted in homogeneous samples of healthy, well educated, Caucasian elders. There is no information on the value of these markers in more typical aging populations representing the broad demographic spectrum who often have multiple comorbidities. Given the aging veteran population, and their increasing need for health care, it is critical to develop accurate diagnostic and predictive models of disease, in order to target treatment and disease management. This application proposes to conduct a longitudinal study of aging veterans to determine if specific neuropsychological and CSF markers can predict transition to Alzheimer dementia and the rate of cognitive, functional and global decline. 150 veteran participants with new onset cognitive complaint will undergo neuropsychological testing and lumbar puncture for the collection of CSF markers of tau and amyloid. They will be characterized by strict neuropsychological criteria as amnestic Mild Cognitive Impairment or nonmnestic Mild Cognitive Impairment. CSF markers of tau and amyloid will be used to define the Alzheimer signature of CSF. Key comorbidities will be assessed as covariates including Apolipoprotein E4, vascular risk factors, the presence of Post Traumatic Stress Disorder and mild Traumatic Brain Injury. Participants will be followed for up to 3 years and assessed at 6 month intervals to determine the rate of change on clinical outcomes and the transition to dementia. We hypothesize that new onset cognitive deficit in both amnestic and non-amnestic domains (i.e. aMCI and naMCI) will predict clinical decline and dementia. We also hypothesize that the CSF biomarker signature will predict clinical decline and dementia in those with cognitive deficits (MCI) regardless of the presence of memory deficit. Cumulative transition rates will be estimated based on the survival curves generated from the Cox models. Rates of cognitive, functional and clinical decline will be compared between amnestic and non amnestic groups and between CSF signature positive and signature negative groups using the generalized estimating equation technique. Additional analyses will compare these markers alone and in combination to determine the best predictor model for dementia in this cohort. These results offer the opportunity to evaluate these markers in a high risk population of veterans who have complex medical needs. It will address the question of which tests and diagnostic approaches have the greatest value in predicting Alzheimer disease and clinical decline.